EngineX-Iluvatar/enginex-mr_series-sherpa-onnx
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Support building GPU-capable sherpa-onnx on Linux aarch64. (#1500)

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Thanks to @Peakyxh for providing pre-built onnxruntime libraries 
with CUDA support for Linux aarch64.

Tested on Jetson nano b01
This commit is contained in:
Fangjun Kuang
2024-11-01 11:16:28 +08:00
committed by GitHub
parent a3c89aa0d8
commit 9ab89c33bc
41 changed files with 537 additions and 291 deletions
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4
sherpa-onnx/csrc/offline-transducer-nemo-model.cc
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@@ -123,7 +123,7 @@ class OfflineTransducerNeMoModel::Impl {
return std::move(logit[0]);
}
std::vector<Ort::Value> GetDecoderInitStates(int32_t batch_size) const {
std::vector<Ort::Value> GetDecoderInitStates(int32_t batch_size) {
std::array<int64_t, 3> s0_shape{pred_rnn_layers_, batch_size, pred_hidden_};
Ort::Value s0 = Ort::Value::CreateTensor<float>(allocator_, s0_shape.data(),
s0_shape.size());
@@ -149,7 +149,7 @@ class OfflineTransducerNeMoModel::Impl {
int32_t SubsamplingFactor() const { return subsampling_factor_; }
int32_t VocabSize() const { return vocab_size_; }
OrtAllocator *Allocator() const { return allocator_; }
OrtAllocator *Allocator() { return allocator_; }
std::string FeatureNormalizationMethod() const { return normalize_type_; }